PODCAST

The Health AI Brief

Stephen Auger

Decoding artificial intelligence for busy medical professionals

health & fitness medicine

All Episodes

2:35

042 Activation Functions - To Fire or Not To Fire

The Health AI Brief ·

2025/12/12

How does AI capture the complex, non-linear reality of human biology? Today we break down Activation Functions, the mathematical trigger that decides if a neuron fires, enabling deep learning to see patterns.#DeepLearning #CardiologyAI #ECG #MedTech #FutureOfMedicine #ai in medicine Music generated by Mubert https://mubert.com/renderhealthaibrief@outlook.com

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2:24

041 Neurons & Weights - The Synapse of AI

The Health AI Brief ·

2025/12/11

Deep learning isn't magic; it's math. Today we explain the "Neuron" and "Weight", the basic building blocks that allow AI models to learn, and the concept of Backpropagation.#DeepLearning #NeuralNetworks #AIExplained #MedicalAI #Doctors #ai in medicine Music generated by Mubert https://mubert.com/renderhealthaibrief@outlook.com

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2:29

040 K-Means - The Automated Triage Nurse

The Health AI Brief ·

2025/12/09

How do we find new disease subtypes in massive datasets? We explain K-Means Clustering and the power of unsupervised learning in discovering new patient phenotypes.#PrecisionMedicine #BigData #Clustering #Sepsis #MedEd #ai in medicine Music generated by Mubert https://mubert.com/renderhealthaibrief@outlook.com

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6:05

Beyond the Benchmark - How do we test a 'superhuman'...

The Health AI Brief ·

2025/12/08

Reference: Gallifant, J. & Bitterman, D.S. (2025). Humanity’s Next Medical Exam: Preparing to Evaluate Superhuman Systems. NEJM AI, 2(11). DOI: 10.1056/AIe2501008When an AI scores 100% on a medical exam but can't navigate a hospital ward, is it really a doctor?Today, we break down a new editorial from NEJM AI by Gallifant and Bitterman. We explore the transition from "recall" to "reasoning" and why the future of AI safety lies in "Interactive Interrogation" and

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2:35

039 SVMs - Drawing the Clearest Line Between Sick and...

The Health AI Brief ·

2025/12/04

When the diagnosis isn't black and white, how does AI decide? Today we explore Support Vector Machines (SVMs), the "Kernel Trick," and how they manage the edge cases in medical data.#SVM #Diagnostics #MedicalImaging #DataScience #HealthAI #ai in medicine Music generated by Mubert https://mubert.com/renderhealthaibrief@outlook.com

en-US

6:08

The Verdict on AI Scribes - Analysing their First...

The Health AI Brief ·

2025/12/03

Everyone is talking about ambient AI scribes, but until now, we’ve relied on marketing hype and small pilots. This week, we dive into two landmark Randomized Controlled Trials published in NEJM AI featuring Abridge, DAX Copilot, and Nabla. The results? Complicated. We explore why these tools might be solving burnout without actually saving time, the hidden "measurement trap" in electronic health records, and why the real revolution isn't about writing notes—it’s about what happens

en-US

2:35

038 Random Forests - The Wisdom of the MDT

The Health AI Brief ·

2025/12/02

Why ask one algorithm when you can ask a thousand? Random Forests and how "ensemble learning" mimics the reliability of a Multi-Disciplinary Team meeting to solve complex cases.#RandomForest #MachineLearning #HealthTech #ClinicalDiagnosis #AI #ai in medicine Music generated by Mubert https://mubert.com/renderhealthaibrief@outlook.com

en-US

2:10

037 Decision Trees - The Algorithms You Already Use

The Health AI Brief ·

2025/11/27

Not all AI is a black box. In this episode, we explain Decision Trees, the transparent, flowchart-style algorithms that mirror clinical reasoning, and why they sometimes "overfit" the textbook.#DecisionTrees #ClinicalDecisionSupport #AIinMedicine #DigitalHealth #MedTech #ai in medicine Music generated by Mubert https://mubert.com/renderhealthaibrief@outlook.com

en-US

2:50

036 Regression - The Statistical Bedrock of AI

The Health AI Brief ·

2025/11/25

Here we break down the difference between linear and logistic regression, their massive role in current guidelines, and why their transparency makes them a clinical favourite.#MedEd #HealthAI #EvidenceBasedMedicine #Regression #ClinicalData #ai in medicine Music generated by Mubert https://mubert.com/renderhealthaibrief@outlook.com

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2:20

035 The Architecture Shift - From Mechanics to Models

The Health AI Brief ·

2025/11/24

We’ve covered the "physiology" of AI learning. Now we move to the "anatomy." We are shifting focus from how models learn to the specific architectures designed for medical tasks. The coming episodes will dissect the differences between the AI that reads X-rays (CNNs) and the AI that writes notes (LLMs) and why clinicians must match the model to the medical problem.#HealthAI #MedEd #DigitalHealth #AIArchitecture #MachineLearning #MedicalInnovation #ClinicalAI#ai in medicine Music

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5:47

The WHO AI Report and Why Governance is Stalling...

The Health AI Brief ·

2025/11/21

Today we break down the massive new WHO report on AI readiness across 50 European countries.There is big ambition, but the gaps are glaring.- Only 8% of countries have a health-specific AI strategy.- 86% cite "legal uncertainty" as the top barrier.- Less than a quarter offer AI training to clinicians.We explore the hurdles, the brilliant case studies from Finland, Turkey, and the UK, and propose a pragmatic path forward. It’s time to move from "pilotitis" to policy.Link to the full

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3:01

034 Regularisation - the antidote to overfitting

The Health AI Brief ·

2025/11/20

How do you stop an AI from overfitting and just memorising data? You penalise it for being too complex. This is "regularisation," the primary antidote to the critical problem of overfitting. In this episode, we explain how regularisation works and why looking for it in a paper's methodology section is a quick way to judge the rigour and quality of the research.#Regularization #AIinHealthcare #MachineLearning #ClinicalAI #HealthTech #Overfitting #DataScience #MedicalEducation #MedEd #ai

en-US

3:04

033 The Bias-Variance Tradeoff - The Specialist vs...

The Health AI Brief ·

2025/11/18

Underfitting (too simple) vs. Overfitting (too complex). These two problems are linked by the "Bias-Variance Tradeoff," the central balancing act of all AI. In this episode, we explain this crucial concept, what bias and variance mean in this context, and how it gives you a powerful new framework for understanding the nature of any AI model's errors.#BiasVarianceTradeoff #AIinHealthcare #MachineLearning #ClinicalAI #HealthTech #DataScience #CriticalAppraisal #MedicalEducation #MedEd #ai

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2:37

032 Underfitting - the overly simplistic intern

The Health AI Brief ·

2025/11/13

We've all heard of AI models that learn too much, but what about models that fail to learn at all? This is "underfitting" – the opposite of overfitting – where a model is too simple for the clinical task. In this episode, we explain this fundamental concept and what it tells you about the AI development process when you see it.#Underfitting #AIinHealthcare #MachineLearning #ClinicalAI #HealthTech #DataScience #ModelTraining #MedicalEducation #MedEd #ai in medicine Music generated by

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2:54

031 Overfitting - the brittle genius

The Health AI Brief ·

2025/11/12

Why do some AI models get 99% accuracy in a study but fail in the real world? The answer is "overfitting" – a critical flaw where a model memorises data instead of learning from it. In this episode, we use the analogy of an over-crammed student to explain what overfitting is and give you the key question you must ask to spot it in any research paper.#Overfitting #AIinHealthcare #MachineLearning #ClinicalAI #HealthTech #CriticalAppraisal #DataScience #MedicalEducation #MedEd #ai in medicine

en-US

6:00

What DeepMind's AI That Mastered Video Games Taught...

The Health AI Brief ·

2025/11/11

Paper - Human-level control through deep reinforcement learning, by Mnih et al 2015, NatureLink - https://www.nature.com/articles/nature14236This week on The Health AI Brief, we're going back to basics. We revisit the landmark 2015 DeepMind paper that taught an AI to master 49 different Atari games from scratch.Find out why this wasn't just about video games, but a foundational breakthrough in making AI stable and generalisable. We explore the core concepts of "experience replay" and

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2:28

030 Actor-Critic Partnership - The Best of Both Worlds

The Health AI Brief ·

2025/11/07

What happens when you combine an AI that can 'do' with an AI that can 'judge'? You get an Actor-Critic partnership, the state-of-the-art in reinforcement learning. We explain how this 'trainee and consultant' model is powering the next generation of dynamic, responsive medical AI.#HealthAI #DigitalHealth #ArtificialIntelligence #ReinforcementLearning #DeepLearning #ClinicalAI #MedEd #MedicalPodcast #ai in medicine Music generated by Mubert

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2:34

029 Policy-Based Methods - Learning How To Act Directly

The Health AI Brief ·

2025/11/05

Forget judging, some AIs learn by doing. 'Policy Gradient Methods' create an 'AI Actor' that learns skills directly, much like a person learning to suture. This is the technology behind AI in robotics and precision medicine. Here's what you need to know.#HealthAI #DigitalHealth #ArtificialIntelligence #ReinforcementLearning #RoboticSurgery #ClinicalAI #MedEd #MedicalPodcast #ai in medicine Music generated by Mubert https://mubert.com/renderhealthaibrief@outlook.com

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5:46

When the Chatbot is More Humane Than the Doctor

The Health AI Brief ·

2025/11/04

What happens when a patient decides an AI chatbot is more "humane" than their doctor? A powerful essay in The Guardian and Rest of World explores one mother's growing reliance on 'Dr. DeepSeek', an AI that is both a comforting, empathetic companion and a source of dangerous medical misinformation.In this episode, we dissect the story's key themes: the "push" from an overburdened healthcare system, the "pull" of AI's infinite patience, and the peril of

en-US

2:34

028 Value-Based Methods and Their Limits - The World...

The Health AI Brief ·

2025/10/30

Some AIs learn by becoming expert judges, calculating a score for every possible clinical decision before making a move. We explain value-based methods, the 'AI Critic,' and why they excel at multiple-choice medicine but falter when the decisions are infinitely complex.#HealthAI #DigitalHealth #ArtificialIntelligence #ReinforcementLearning #DeepLearning #ClinicalAI #MedEd #MedicalPodcast #ai in medicine Music generated by Mubert https://mubert.com/renderhealthaibrief@outlook.com

en-US

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